The work on StyleGAN [1]} revealed certain input conditions that contributed to the generation of super realistic images, improving upon the blurry or distorted images generated by previous works. These conditions are a) images in the dataset should be of similar zoom ratio; b) the input to the GAN should be simple; c) diversity of the data should be balanced.
In our initial experiments with DCGAN [2]}, ProgressiveGAN [3]}, CycleGAN [4]}, and StyleGAN, we observed that if we pass the whole body with the head attached, then the results are blurry and the GAN fails to generate properly. In our experiments we made sure that the dataset is clean enough to have similar zoom ratio on the subject, images are diverse, and we removed any complex distractions, such as the head, before passing to the Poly-GAN inputs.
